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Conference Paper: Snapshot multi-PSF 3D single-molecule localization microscopy using deep learning

TitleSnapshot multi-PSF 3D single-molecule localization microscopy using deep learning
Authors
Ikoma, HayatoPeng, YifanBroxton, MichaelWetzstein, Gordon
Issue Date2020
Citation
Optics InfoBase Conference Papers, 2020, article no. CW3B.3 How to Cite?
AbstractWe propose a neural point spread function (PSF) engineering approach for 3D single-molecule localization microscopy. Our approach jointly optimizes the PSFs of multiple optical paths in a microscope with a differentiable localization algorithm.
Persistent Identifierhttp://hdl.handle.net/10722/315366

 

DC FieldValueLanguage
dc.contributor.authorIkoma, Hayato-
dc.contributor.authorPeng, Yifan-
dc.contributor.authorBroxton, Michael-
dc.contributor.authorWetzstein, Gordon-
dc.date.accessioned2022-08-05T10:18:37Z-
dc.date.available2022-08-05T10:18:37Z-
dc.date.issued2020-
dc.identifier.citationOptics InfoBase Conference Papers, 2020, article no. CW3B.3-
dc.identifier.urihttp://hdl.handle.net/10722/315366-
dc.description.abstractWe propose a neural point spread function (PSF) engineering approach for 3D single-molecule localization microscopy. Our approach jointly optimizes the PSFs of multiple optical paths in a microscope with a differentiable localization algorithm.-
dc.languageeng-
dc.relation.ispartofOptics InfoBase Conference Papers-
dc.titleSnapshot multi-PSF 3D single-molecule localization microscopy using deep learning-
dc.typeConference_Paper-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.scopuseid_2-s2.0-85118656043-
dc.identifier.spagearticle no. CW3B.3-
dc.identifier.epagearticle no. CW3B.3-

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